Modified Half-Cauchy Chen (MHCC) Distribution with Applications to Lifetime Dataset

Abstract

In this article, we have recommended an innovative versatile distribution called Modified Half-Cauchy Chen distribution by modifying half-Cauchy Chen distribution. The recommended distribution's various properties are derived and analyzed. The recommended distribution's parameters are ascertained by applying the maximum likelihood estimation (MLE) approach. Furthermore, the performance of the Modified Half-Cauchy Chen distribution is compared against other distributions using various statistical measures. These measures consist of the Corrected Akaike Information Criterion (CAIC), the Kolmogorov-Smirnov (K-S) test, the Bayesian Information Criterion (BIC), and the Akaike Information Criterion (AIC). The results consistently demonstrate the superior fit of the Modified Half-Cauchy Chen distribution to the data. The goodness-of-fit analysis is carried out on a real data set in order to evaluate the innovative distribution's applicability. The Modified half-Cauchy Chen distribution is shown to perform better than a few other known distributions. R programming software is used to help with every computation.